MCA in Data Science and Artificial Intelligence
Master of Computer Application (MCA) with Specialization in Data Science and Artificial Intelligence is a 2-year postgraduate course offered by the School of Computer Application, Babu Banarasi Das University in collaboration with IBM. This course is designed to make the professional technically sound in advanced learning systems that are based on algorithms of data science and Artificial Intelligence.
The Global data science industry has consistently been among the fastest growing industries. The market is particularly strong for technology professionals who straddle computer science, applications, and data science.
This course will help the professional to integrate data science models into computer systems. It will develop both sound computing foundations and an incisive analytical mind. The program first builds foundations with a comprehensive software & computer applications curriculum and adds a deep-dive into data science, analytics techniques using artificial intelligence approach.
School of Computer Application has collaborated with IBM which is a leading name in this field. IBM is moving with the idea of helping organizations that are data-driven. With this collaboration, SoCA, BBDU is guiding students into a new direction of a more innovative and effective way of handling data.
It is a practical industry-focused curriculum that is appreciated by a panel of academic as well as industry experts.
Course Details
| School Name: | School of Computer Applications |
| Course Length: | 2 Years |
| Session Start | July |
| Course Type: | Full Time |
| Eligibility Criteria: | BCA or Graduation with CS/ IT or equivalent courses, rest all criteria will be as per UGC and State Government Norms |
| Programme Fee: | Rs. 70, 250/- Per Semester |
| Syllabus | SCA BBDU MCA (DS and AI) 2021-22 Academic Session-2024-25 as per NEP-2020 |
Program Details/FAQs
- Software Developer
- Web Developer
- System Analyst
- Network Administrator
- Database Administrator
- Technical Support Engineer
- UI/UX Designer (with additional skills)
Entry-level salaries typically range between ₹2.5 to ₹5 LPA inIndia,depending on your skills and location.
- MCA (Master of Computer Applications)
- M.Sc. (IT/CS)
- MBA (for managerial roles in IT companies)
- Specialized courses like Data Science, Cybersecurity, Cloud Computing
No prior programming skill is required to join,you will be taught from the basics. Having a programming mindset helps.
Yes, in the final semester.
Yes. Labs, mini-projects, final-year capstone, and internships are part of the curriculum.
C, Java, Python, HTML, JavaScript, PHP, SQL, etc.
BCA is a four-year program.
Both are good, but B.Tech. is more engineering-oriented and involves hardware and deeper technical concepts. BCA is more focused on software and applications.
Many international companies actively recruit BCA graduates, especially in tech hubs like the USA, Canada, UK, and Australia.
Graduates can pursue roles such as:
- Cyber Security Analyst
- Information Security Officer
- Network Security Engineer
- Ethical Hacker
- Penetration Tester
- IT Auditor
- Cyber Forensics Expert
Yes, you can pursue:
- MCA (Master of Computer Applications)
- MCA or M.Sc. in Cyber Security or Information Security
- MBA in IT or Systems
- Specialized certifications (e.g., CEH, CISSP, CISA)
It depends on your career goals. If you're interested in digital safety, ethical hacking, or data protection, the specialized BCA in Cyber Security offers a targeted pathway into a high-demand field.
Entry-level salaries range from INR 3 to 6 LPA in India, and can grow significantly with experience and certifications.
Yes, in the final semester.
Yes. Labs, mini-projects, final-year capstone, and internships are part of the curriculum.
C,Python, HTML, JavaScript, PHP, Linux & Shell Programming, Android Programming & R Programming.
Both are good, but B.Tech. is more engineering-oriented and involves hardware and deeper technical concepts. BCA (CS & F) is more focused on application oriented with specialization like Cloud, Forensic and Security.
BCA(Cyber Security & Forensics) is a four-year program.
No, it starts with basic concepts and builds up. Prior knowledge is helpful but not mandatory.
Graduates can work as:
- Data Analyst
- AI/ML Engineer (with additional skills)
- Business Intelligence Analyst
- Software Developer
- Database Administrator
- Data Engineer
Yes. Common paths include:
- MCA (Master of Computer Applications)
- MCA or M.Sc. in Data Science or AI
- MBA (for managerial roles in tech firms)
- Certifications in AI/ML, Data Engineering
In India, the starting salary typically ranges between 3.6 LPA, depending on skills, internships, and the hiring company.
Yes. Labs, mini-projects, final-year capstone, and internships are part of the curriculum.
Yes, in the final semester.
C, Java, Python, R Programming, SPSS, HTML, JavaScript, PHP, SQL and Linux & Shell Programming.
Both are good, but B.Tech. is more engineering-oriented and involves hardware and deeper technical concepts. BCA (Data Science & Artificial Intelligence) is more practical and application focused with Machine Learning, Artificial Intelligence and Data Science.
BCA (Data Science & Artificial Intelligence) is a four-year program.
No, it starts with basic concepts and builds up. Prior knowledge is helpful but not mandatory.
- Software Developer / Engineer
- Data Scientist / Analyst
- System Analyst
- Web or App Developer
- Database Administrator
- Cybersecurity Analyst
- AI/ML Engineer
- IT Consultant
- DevOps Engineer
Yes, many universities offer PhD programs in Computer Science, AI, or related areas post-MCA.
- Entry-level salary: ₹4–8 LPA
- With experience or specialization: ₹10–20+ LPA
- Salary depends on skills, internships, and company profile
Yes, in the final semester.
Yes. Labs, mini-projects, final-year capstone, and internships are part of the curriculum.
Java, Python, SQL, C# and Android Programming.
Yes, MCA is a great option for individuals interested in IT and Computer Science. It opens up many opportunities for jobs in software development, data analysis, and other IT-related fields, which have high demand in the market.
Yes, you are eligible for NET/JRF for Computer Science and Applications.
Yes, MCA graduates are eligible for many state and central government jobs including those in IT department, PSU exams and teaching positions.
M.Tech.(CSE) is more engineering focused where as MCA is application and software focused. Both are respected and recognized for technical role.
- Software Developer / Engineer
- Data Scientist / Analyst
- System Analyst
- Web or App Developer
- Database Administrator
- Cybersecurity Analyst
- AI/ML Engineer
- IT Consultant
- DevOps Engineer
- Entry-level salary: ₹4–8 LPA
- With experience or specialization: ₹10–20+ LPA
- Salary depends on skills, internships, and company profile
Yes, in the final semester.
Yes. Labs, mini-projects, final-year capstone, and internships are often part of the curriculum.
Yes, many universities offer PhD programs in Computer Science, AI, or related areas post-MCA (Data Science & Artificial Intelligence).
Java, Python, HTML, JavaScript, PHP, SQL and C#.
MCA (Data Science & Artificial Intelligence) is a 2-year postgraduate course focused on areas such as machine learning, artificial intelligence, data science and emerging new technologies.
The program covers subjects like programming languages, data structures, database management, software engineering, networking, artificial intelligence, machine learning, and web development.
Yes, MCA (Data Science & Artificial Intelligence) is a great option for individuals interested in IT and computer science. It opens up many opportunities for jobs in software development, data analysis, and other IT-related fields, which have high demand in the market.
Yes, this program is recognized by UGC.
| PO(Program Outcomes) | |
|---|---|
| PO1 | Computer Application Knowledge: Apply the knowledge of mathematics and computing fundamentals to various real-life applications for any given requirement. |
| PO2 | Problem analysis: Expertise to transform complex business scenarios and contemporary issues into problems, investigate, understand as well as propose integrated solutions using upcoming technological methods. |
| PO3 | Design/Development of Solutions: Design applications for any desired needs with appropriate considerations for any specific need on societal and environmental aspects |
| PO4 | Conduct Investigations of Complex Computing Problems: Ability to devise and conduct experiments, interpret data and provide well-informed conclusions. |
| PO5 | Modern Tool Usage: Integrate and apply efficiently the contemporary IT tools to all computer applications. |
| PO6 | Perennial Learning: Involve in perennial learning for continued career development and progress as a computer professional. |
| PO7 | Individual and Team Work: Function effectively both as a team leader and team member on multidisciplinary projects to demonstrate computing and management skills. |
| PO8 | Environment and Sustainability: Utilize the computing knowledge efficiently in projects with concern for societal, environmental, and cultural aspects. |
| PO9 | Project Management: Function competently as an individual and as a leader in multidisciplinary projects |
| PO10 | Innovation: Create and design innovative methodologies to solve complex problems for the betterment of society |
| PO11 | Entrepreneurship: Apply the inherent skills with absolute focus to function as a successful entrepreneur. |
| PO12 | Life-long Learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in technological change. |
| PSO (Program Specific Outcomes) | |
|---|---|
| PSO1 | Explore technical comprehension in varied areas of Computer Applications and experience a conducive environment in cultivating skills for thriving career and higher studies. |
| PSO2 | Comprehend, Explore and build up computer programs in allied areas like Algorithm, System software, Multimedia, Web Design and Data analytics for efficient design of computer-based systems of varying complexity. |
